MOOSES™ (Multi-Option Observation System for Experimental Studies) is a robust software solution developed by the Vanderbilt Kennedy Center to streamline real-time event data collection and analysis. Authored by Jon Tapp, Director of Computer Services and lead software developer, it empowers researchers in psychology, education, and behavioral sciences to capture accurate, multidimensional data efficiently, overcoming the complexities of observational study management.
Key features include:
- Real-time data collection on desktops, laptops, handheld PCs, or Windows tablets (Windows 95 or higher).
- Multi-dimensional analysis with IOA calculations, lag counting, and SALT/ODF format support.
- Seamless integration with ProcoderDV™ for audio/video data analysis (procoderdv.vueinnovations.com).
Included Tools: MOOSES™ provides advanced analytical tools to enhance research outcomes, with results exportable to reports or spreadsheets:
- Frequency and Duration: Observers input event codes in real time, generating data files that calculate frequencies and durations for each session. A built-in list management system processes multiple sessions simultaneously, with optional pooling of results. Event durations are computed within mutually exclusive, exhaustive code groups accounting for the full session time, supporting up to 48 event type codes. Outputs are available as printer-friendly reports or comma-separated data files for spreadsheet or statistical software.
- Inter-Observer Agreement (IOA): Compares data from two observers using two methods: (1) time-window comparisons, tallying matches within a time window around the first observer’s event, calculating agreement ratios per event code; or (2) time-unit comparisons, matching each time unit across observers’ files to determine agreement or disagreement. Results display in a square matrix with agreements on the diagonal and disagreements off-diagonal, including agreement ratios and Kappa statistics. Outputs are available as lists, reports, or comma-separated data files.
- Multi-Group Frequency and Duration: Analyzes overlapping durations across groups (e.g., student aggression when a teacher is present versus absent) in classroom or similar settings. Results are displayed as lists, printer-friendly reports, or comma-separated data files, with graphical representations for enhanced insights.
- Sequential Analysis: Examines how events influence each other in a data stream (e.g., testing if staff prompts trigger self-injurious behavior), using Yule’s Q statistic to measure sequential associations. Results are provided as lists, reports, or comma-separated data files for research applications.
Benefits: MOOSES™ simplifies complex observational studies, reducing errors and accelerating data processing for publication-ready insights. Its versatile tools support diverse research scenarios, making it essential for academic and applied studies. For more information, visit the Vanderbilt Kennedy Center or explore licensing options on our Licensing Options Page. Contact us at Contact Us for support.